People are ever more reliant on computing devices, such as mobile devices, for their day-to-day activities. Various service content items are available for users via these computing devices. As one example of such service content items, mobile devices can run software applications, or apps, which are designed to help users perform tasks. Other examples include songs, movies, images, documents, books, content cards, and the like. With the ever increasing amount of service content items available for users from content providers via platforms such as Windows Store by Microsoft®, Microsoft Cortana, and the like, it can be difficult to provide the users with those that are most useful. Thus, users may consume extensive computing resources of their devices and of content providers searching for, downloading, and/or evaluating service content items attempting to discover those that are useful or desirable.
When sufficient service content items are recommended to users, their consumption of the computing resources is reduced. However, insufficient recommendations can have the opposite effect on resource consumption. Recommendations may be made using crowd-sourced data from users. However, often times recommendation systems lack the data points required to reliably provide sufficient recommendations to users. In these cases, the systems may refrain from providing recommendations as an alternative to providing insufficient recommendations.